Method and apparatus for categorizing items of clothing and method and apparatus for selecting footwear having an improved fit

ABSTRACT

A method and a device for categorizing articles of clothing and a method and a device for selecting footwear having an improved fit are specified. A parameter describing the fit and/or the size of an article of clothing is acquired on the basis of a measurement carried out on the article of clothing in question. This measurement is performed for a plurality of articles of clothing of different manufacturers but having an identical manufacturer clothing size, a plurality of different manufacturer clothing sizes being furthermore considered. A frequency analysis for the occurrence of specific values of the at least one parameter is then performed for articles of clothing having an identical manufacturer clothing size. The articles of clothing are categorized by a new allocation of the clothing size, a new clothing size being allocated to the articles of clothing in such a manner that the parameters of the articles of clothing provided with the new clothing size within this new clothing size have a smaller dispersion.

The invention relates to a method and to a device for categorizingarticles of clothing. The invention furthermore relates to a method andto a device for selecting footwear having an improved fit.

TECHNICAL BACKGROUND

For the selection of a fitting shoe, the standardization information ofthe “shoe size” is usually taken as a basis to find the right sizevariant for a shoe model. The “shoe size” is intended to describe acomplex three-dimensional shoe inner shape and to make the lattercomparable. However, since different shoes having the same shoe sizeinformation often represent shoe inner shapes having very differentforms and also different lengths, the client can use this informationmerely as very rough approximation. Usually, the client has no otheralternative than to classify the fit of a shoe as fitting or not fittingby trying on by trial and error.

While this physical try-on is possible and common in thebrick-and-mortar business and merely makes the selection process moredifficult and longer, this is in principle no longer possible in themail-order business, in particular in the purchase of shoes based on theInternet, due to the spatial separation of goods and client. As aresult, the Internet buyer often simultaneously orders several shoesizes/shoe widths and returns the shoes which do not fit at the cost ofthe mail-order company. In this way, very high costs are incurred by themail-order company due to the required logistics, the necessary visualcheck and the new packaging of returns and the new storing. These highcosts constitute a considerable charge of this business model otherwisemodern and corresponding to the spirit of the times.

The worldwide usual standardization methods for shoes such as the EU, USor UK shoe size, e.g. the so-called Paris point in France or the unit ofmeasurement barleycorn in the Anglo-Saxon region, have been developed todetermine the last or shoe inner length in order to describe differentshoe shapes and to make them comparable with each other. Further shoesize systems are for the most part derived from the mentioned systems.As consistent systems are involved, they may be converted into eachother using conversion tables.

In these conventional standardization methods, the complexthree-dimensional shape of the shoe interior is described by means of aone-dimensional linear dimension. To this end, three reference valuesare in particular used in practically all shoe size systems:

-   -   the length of the shoe last is measured, which is a production        mould and fills the shoe interior during manufacture,    -   the length of the shoe interior is measured,    -   conclusions are empirically drawn about the shoes to be        standardized by means of so-called test runners the foot length        of which is measured. These foot lengths are used as shoe sizes        depending on which shoes fit the test runners with a known foot        length.

These standardization methods with their historically and regionallydifferent origins differ in the unit of measurement used and the zeropoint for the determination of the length.

The traditional shoe size systems are characterized in that

-   -   units of length and appropriate intervals are fixed, wherein the        latter is for example 6.66 mm in a EU shoe size,    -   these units of length can be converted into each other,    -   the systems are now widely used, and    -   a wide practical knowledge in dealing with these systems is        available.

These shoe size systems as standardization methods however have thedrawback that they are not standardized and not clearly described, inparticular:

-   -   that with respect to the object to be measured (last, shoe        interior or feet),    -   the measuring points of the linear dimension are not clearly        defined,    -   they do not explicitly take the so-called functional or        fashionable additions into account, which are added to the toe        region to facilitate the dynamic movement or are added for        fashionable reasons so as to modify the length,    -   different units of measurement prevail on the market under the        same name, such as in the US shoe size system in which in        particular the big sports shoe manufacturers often use 10 mm as        scaling instead of half a barleycorn (approx. 8.466 mm),    -   the relatively complex three-dimensional inner shape of the shoe        is reduced to very few dimensions, in most cases only to the        length, by means of a strong simplification,    -   inaccuracies are produced by rounding to half or full sizes upon        conversion from one to another sizing system, and    -   the standardization, i.e. the definition of the shoe size of a        specific model is performed by the respective manufacturer        himself and in very different ways.

Due to these limitations of the used standardization methods for shoesizes, shoes are today offered on a large scale on the market, whichhave shoe inner shapes that differ considerably despite identical shoesize designations.

There have been many attempts to improve the selection of a fitting shoesize of a desired shoe model by the client. The processes and methodscan be subdivided into the two following approaches:

approach a): the individual comparison between the foot of the clientand the shoe models offered,

approach b): the numerical description of feet and shoes by means of“shoe sizes” or other categories, and the assignment thereof in classes.

An illustrative example for approach a) is the method used in theInternet shop for children's shoes of “Ricosta” of Donaueschingen (cf.also: www.ricosta.de/ricosta-welt/fussmessung-online). Here, for thepurpose of a graphical-visual comparison, the naked child's foot isplaced on or held in front of the flat screen of the client's Internetcomputer. A single geometric calibration is previously carried out onthe computer screen using a calibration aid. A template of a schematicsole the length and the width of which can be modified using the mouseis than represented on the screen. The client can modify the approximatelength and width of the schematic sole of the child's foot representedon the screen by means of two slide controls, and can determine thelength and width of the child's foot by a purely visual comparison withthe child's foot present in front of the screen. These specificationsare used for the ensuing order. Due to this direct comparison, thismethod does in principle not require further details such as the shoesize.

Also the formerly common methods of X-ray observation of the footskeleton within a shoe put on can be classified under approach a). Thesemethods are however no longer used due to the high radiation exposure.There are alternative approaches to visually represent the position andshape of the foot within the shoe using passive thermal imaging camerasso that no damaging radiation exposure occurs (cf. for example U.S. Pat.No. 6,975,232 B1).

Several further method variants also exist as to approach a). The footis for example geometrically measured by means of a measuring device andcompared with the geometrical data of the shoe candidates to beconsidered. These systems are usually classified in two- andthree-dimensional foot measuring devices. The selection of fitting shoesis performed by a comparison of the measuring information about the foot(e.g. 2D-sole shape, 3D-foot model, etc.) with the available geometricmeasurement data of the lasts used for the manufacture or the measuredshoe interiors.

The Canadian company Vorum Research Corporation offers a 3D-comparisonbetween the foot and the shoe (cf. alsowww.vorum.com/english/footware/matching-system.php). The entire surfaceof a foot is statically measured using a three-dimensional foot scannerand is then compared with the available three-dimensional lastinformation and is evaluated with respect to its fit.

The second approach b) relates to the conventional approaches as to theclassification of feet and shoes by means of a standardized shoe size.This approach proceeds on the assumption that knowing the shoe size, theassignment of a fitting shoe model via a categorization is simple.

Examples for this classical approach b) are the established shoe sizesystems described above, such as the US, UK or EU shoe size systems. Incase the shoe size is unknown, the length and partially the width offeet are measured using simple means (measuring tape, Brannock verniercaliper, etc.) to assign a shoe size and a width to them. All shoemodels labeled with shoe size 42 should fit a foot having the standardsize 42, which is however often not the case in practice.

It remains to note that the approaches a) and b) are satisfactoryneither with regard to the obtainable fitting quality, nor with regardto the simple handling desired by the client. In particular in themail-order business where it is not possible to try the footwear on,erroneous fits and extremely costly returns of the goods therefore oftenoccur.

SUMMARY

The object of the invention is to specify a device and a method whichreduce the difficulties existing in the prior art.

According to one aspect of the invention, a method of categorizingarticles of clothing with regard to their clothing size is specified.This clothing size, for example a dress size for outer clothing or ashoe size for shoes, describes a fit and/or a size of the article ofclothing. Each article of clothing is provided with a specificmanufacturer clothing size on the part of the manufacturer. Within thecontext of the method according to the invention, a basic population ofarticles of clothing is considered which comprises articles of clothinghaving different manufacturer clothing sizes. Articles of clothing ofdifferent manufacturers for each manufacturer clothing size arerespectively included in this basic population. First, at least oneparameter describing the fit and/or the size of the article of clothingis acquired on an article of clothing from this basic population bymeans of a measurement performed on the article of clothing concerned.This at least one parameter is assigned to the manufacturer clothingsize of the article of clothing concerned. These two steps of detectionand assignment are performed for a plurality of articles of clothinghaving an identical manufacturer clothing size. Articles of clothing ofdifferent manufacturers or suppliers are here taken into account. Inother words, articles of clothing having the same size but differentmanufacturers or suppliers are thus analyzed within one manufacturerclothing size. Furthermore, the two steps of detection and assignmentare performed for a plurality of articles of clothing having differentmanufacturer clothing sizes. A frequency analysis is then performed asto the occurrence of specific values of the at least one parameter forsuch articles of clothing which have an identical manufacturer clothingsize but are offered by different manufacturers or suppliers. Thisfrequency analysis is performed for a plurality of manufacturer clothingsizes. In the ideal case, there is then one respective frequencydistribution and one frequency analysis for each examined manufacturerclothing size, the frequency analysis being performed on the basicpopulation mentioned which includes articles of clothing of differentmanufacturers. The articles of clothing are then re-categorized by a newallocation of a new clothing size which may possibly differ from themanufacturer clothing size. The categorization is carried out such thatthe new clothing size is assigned to the articles of clothing for whichthe at least one parameter within the newly allocated clothing size hasa smaller dispersion than was the case in the original manufacturerclothing size.

In other words, the new allocation of the clothing size is carried outsuch that the frequency distribution of the at least one parameteroverlaps less strongly for neighboring new clothing sizes than was thecase for the original manufacturer clothing sizes. In the terminology ofstatistics and classification, this means that the resulting frequencydistribution in the new clothing size has a reduced intra-class varianceand an increased inter-class variance. In the present case, the class isthe new clothing size.

Advantageously, using the method of categorizing articles of clothing,it is possible to reduce the negative influence on the fit resultingfrom deviations of fit in identical or similar articles of clothing ofdifferent manufacturers which are present despite the same manufacturerclothing size. The consumer can orientate himself/herself towards thenewly allocated clothing size instead of the original manufacturerclothing size. This is particularly advantageous for the onlinemail-order business since in this way, there is a higher probabilitythat the consumer is provided with a fitting article of clothing, andthe number of returns can be reduced. At the same time, the consumer canorientate himself/herself on the basis of the familiar clothing size,such as the dress size or the shoe size, e.g. The consumer need notprovide further information or take further actions such as ameasurement or a visual comparison. Due to the performed re-allocationof the clothing size which constitutes a virtual “re-labeling”, theconsumer can be provided with a considerably higher probability with anarticle of clothing that corresponds to the fit he/she has assumed byexperience which is for him/her hidden behind the clothing sizeindication in question.

In a very simplified illustration, the method according to aspects ofthe invention is based on the evaluation of the following findings. Inmodern electronic mail-order business, a specific article of clothing isoffered by a large number N of different manufacturers. Despitegenerally identical geometries, there are relatively great differencesbetween the articles of clothing though they are provided with the samemanufacturer clothing size. Typically, N>20 different manufacturersoffer a specific article of clothing in the common clothing sizes. Thebasic population N is large enough to obtain, by measurements,statistically solid findings and systems as to these manufacturerclothing sizes which differ considerably from manufacturer tomanufacturer. On the basis of empirical analyses, it could be provedthat for one respective specific article of clothing from the productionof the N manufacturers with their own respective manufacturer clothingsize, the center of a frequency distribution of physically measurabledimensions is near a “real” clothing size. This “real” clothing sizecorresponds to the fit and size which the client expects from thisclothing size. According to aspects of the invention, these findings areused to provide the client with articles of clothing having on average abetter fit despite the basically unreliable manufacturer clothing sizevia a virtual re-labeling, i.e. a re-allocation of the clothing size.

Advantageously, in the method of categorizing articles of clothing, astatistical key figure characterizing the frequency distribution, e.g. apercentile value or a mean vale of the at least one parameter from therespective frequency distribution can be determined for the plurality ofmanufacturer clothing sizes. In case several parameters are acquired,several statistical key figures are determined from the correspondingfrequency distributions. The at least one statistical key figure isassigned to a corresponding new clothing size. Furthermore, it ispossible to determine a deviation of the at least one parameter from thecorresponding statistical key figure of the parameter for differentmanufacturer clothing sizes. That new clothing size is assigned to thearticle of clothing, for which this deviation is minimal.

It is furthermore possible to perform the acquisition of the parameterdescribing the fit and/or the size on identical or similar articles ofclothing of different manufacturers. The parameter(s) may for example beacquired on a specific type of article of clothing, for example a men'sjacket or a women's ankle boot of different manufacturers. Acategorization may then be performed for all identical or similararticles of clothing of the corresponding manufacturer. In this way,information such as that the men's low shoe of type A of manufacturer Bin shoe size 42 sizes small and rather corresponds as to its inner shapeto shoe size 41, can be acquired and used to re-categorize all men's lowshoes of type A of manufacturer B and to allocate the new shoe size 41rather than the manufacturer shoe size 42 to these shoes.

According to a further embodiment, the method relates to thecategorization of shoes. The manufacturer clothing size is in this casethe manufacturer shoe size defined on the part of the manufacturer. Toreduce a negative influence on the fit due to inner shape deviationsexisting despite identical manufacturer shoe sizes, an inner shape of ashoe can be detected in a first step. This step may for example beperformed using a shoe interior scanner. At least one parameter is thendetermined, which describes the shoe interior dimension. This at leastone parameter is assigned to the manufacturer shoe size. These two stepsare performed for identical or similar shoe models from the productionof different manufacturers and for different manufacturer shoes sizes. Afrequency analysis for the occurrence of specific values of the at leastone parameter is then performed for shoes of different manufacturershaving identical manufacturer shoe sizes. Moreover, frequency analysesare performed for the shoes in the different manufacturer shoe sizes,but for different manufacturers or suppliers. A categorization of theshoes is realized by a new allocation of the shoe sizes, a new shoe sizebeing assigned to the shoes such that the parameters of the shoesprovided with the new shoe size within this new shoe size have a smallerdispersion than in the original manufacturer shoe size. The frequencydistributions of the parameters of neighboring new shoe sizes overlapless strongly than is the case in the original manufacturer shoe sizesalso in that case.

An application of the method of categorizing shoes is particularlyadvantageous, since there is no standardized and uniform shoe sizesystem for shoes.

According to a further advantageous embodiment, at least one shoe pershoe model, per manufacturer shoe size and per manufacturer isrepresentatively measured for this shoe model, for this manufacturer andfor the shoe size thereof using a shoe interior scanner. The parametersdescribing the shoe interior dimension comprise at least oneanatomically relevant quantity. In the context of a frequency analysisperformed, a one-dimensional frequency function is formed for the chosenanatomically relevant quantity. A membership function is determined. Thelatter defines a range of values for the chosen anatomical quantity.Those values characterizing the anatomically relevant quantity whichmatch for the most manufacturers are within this range of values. Inother words, a predominant number of the values matching for mostmanufacturers are within this range of values. The membership functioncan be fixed on the basis of a threshold value of 50% or 90%, forexample. The membership function is assigned to the new shoe size. Acategorization of the shoes is then carried out by a new allocation ofthe shoe size. This re-allocation is carried out such that a newone-dimensional frequency function for shoes within the new shoe sizeand for all manufacturers considered has a smaller dispersion than theoriginal one-dimensional frequency function.

An anatomically relevant quantity may for example be the interiorlength, the ball circumference, the big toe angle, the heel height, theheight profile of the footbed etc. It is accordingly possible toconsider multidimensional frequency distributions.

According to a further embodiment, at least one shoe per shoe model, permanufacturer shoe size and per manufacturer is measured using a shoeinterior scanner, n>=2 interior dimensions being extracted from thesemeasurements. An n-dimensional frequency function of the n chosenanatomical quantities is accordingly formed for each shoe size and forall manufacturers. A maximum of this n-dimensional frequency function isdetermined, and an n-dimensional membership function is fixed whichdefines that range of values of the n anatomical quantities whichmatches for most manufacturers for the manufacturer shoe sizeconsidered. For the definition of the n dimensional membership function,appropriate limit values may in turn be used, wherein one individuallimit value may be determined for each dimension. The show size is thenre-determined so that the n interior dimensions within the newlydetermined shoe size have a smaller dispersion than was the case in theoriginal manufacturer shoe sizes.

Furthermore, the method of categorizing articles of clothing mayadvantageously be used for protective clothing or medical parts adaptedto the body, such as supports, splints or protectors.

A method of selecting footwear having an improved fit is particularlyadvantageous, in particular with regard to the use in the onlinemail-order business. In this method according to a further aspect of theinvention, the shoes are first re-categorized as to the shoe size inaccordance with the method of categorizing articles of clothing. Uponrequest for a specific shoe size, in particular such footwear is offeredto the user the new shoe size of which corresponds to the request of theuser. In other words, such footwear is offered to the user, theparameter describing the actual fit of which most likely corresponds towhat is assumed behind the shoe size in question. The probability tooffer fitting footwear to the user may be increased.

According to a further aspect of the invention, a device forcategorizing articles of clothing with regard to their clothing size isspecified. The device comprises at least one scanner for acquiring atleast one parameter which describes the fit and/or the size of anarticle of clothing. The device is adapted to consider a basicpopulation which includes articles of clothing having differentmanufacturer clothing sizes. Articles of clothing of differentmanufacturers or suppliers in each of the manufacturer clothing sizesare included in this basic population. The device furthermore has aprocessing unit which is adapted to assign the at least one acquiredparameter to the manufacturer clothing size. The processing unit isfurthermore adapted to perform a frequency analysis for the occurrenceof specific values of the at least one parameter for articles ofclothing of different manufacturers which however have an identicalmanufacturer clothing size. This frequency analysis is moreoverperformed for a plurality of manufacturer clothing sizes. The articlesof clothing are finally categorized by a new allocation of the clothingsize. The new clothing size is assigned to the articles of clothing suchthat the parameters of the articles of clothing provided with the newclothing size within the re-allocated clothing size have a smallerdispersion than within the original manufacturer clothing size.

The device for categorizing articles of clothing according to aspects ofthe invention is in particular adapted to categorize shoes. In thisrespect, the scanner is preferably a scanner for acquiring an innershape of shoes which can furthermore be adapted to determine at leastone parameter which describes the shoe interior dimension. Thisparameter is assigned to the manufacturer shoe size on the part of theprocessing unit. A frequency analysis for the occurrence of specificvalues of the at least one parameter is then performed for shoes havingan identical shoe size. A categorization of the shoes is carried out bya new allocation of the shoe size, a new shoe size being assigned to theshoes in such a manner that the parameters of the shoes provided withthe new shoe size within this new shoe size have a smaller dispersionthan in the original manufacturer shoe size.

According to a further aspect of the invention, a device for selectingfootwear having an improved fit is specified. It comprises a device forcategorizing articles of clothing according to aspects of the inventionand furthermore an input unit and an output unit. The input unit isadapted to receive information about a shoe size desired by a user. Theprocessing unit is adapted to offer the user information about footwearthe new shoe size of which corresponds to the shoe size desired by theuser via the output unit.

Identical and similar advantages as already mentioned with regard to themethod according to aspects of the invention are also applicable in anidentical or similar manner to the devices according to aspects of theinvention and are therefore not repeated here.

SHORT DESCRIPTION OF THE DRAWINGS

The invention will be described in detail below with reference to thedrawings illustrating preferred example embodiments, in which:

FIG. 1 shows a frequency distribution of the shoe inner length forwomen's ankle boots of different manufacturers and differentmanufacturer shoe sizes,

FIG. 2 shows selected frequency distributions (FIG. 2A) and themembership functions thereof (FIG. 2B),

FIG. 3 shows a two-dimensional frequency distribution for a shoe innerlength and a ball circumference for women's ankle boots of differentmanufacturers and different manufacturer shoe sizes, and

FIG. 4 shows individual measuring points of the frequency distributionof FIG. 3 in a 2D-plot (FIG. 4A), the determination of membershipfunctions using methods of clustering (FIG. 4B), and a schematicillustration of a subsequent re-allocation of shoe sizes on the basis ofa statistical analysis of the determined frequency distributions (FIG.4C).

DETAILED DESCRIPTION

The realization of a method according to one example embodiment is to bedescribed below as an example for the shoe model “women's ankle boot”.To the time of the analysis, the type of shoe was offered in an Internetshop by 51 different manufacturers in different sizes and designvariants. The extensive studies of the interior dimensions have beenperformed on 874 shoes using a shoe interior scanner working in anoptical and non-destructive manner, which is for example described indocument WO 2009/006989 A1. The measurements have shown that the sameshoe model manufactured by different shoe manufacturers has verydifferent shoe inner lengths for an identical manufacturer sizeindication, i.e. a labeled shoe size. By way of alternative to theexplicit measurement, it is also possible to grade the required interiordimensions from neighboring measured sizes of the same shoe models asfar as reliable grading methods exist for the shoe models concerned.

FIG. 1 shows a frequency distribution of the shoe inner lengths Lmeasured by means of the interior scanner for women's ankle boots inshoe sizes S from EU 36 to EU 41, manufactured by 36 different shoemakers. The dispersion of frequency H of the measured shoe inner lengthsL differs for the different manufacturers by up to three EU-shoe sizes.In these examinations, it could furthermore be observed that comparedwith the unsystematic labeling of the different manufacturers, theactual production tolerances are negligible. Difficulties in terms offit are largely due to imprecise manufacturer size indications. Withthis respect, it is possible according to a further example embodimentto measure a shoe in a representative way for a shoe size of a specificmanufacturer and to assume a same or identical parameter for theappropriately labeled shoes of this manufacturer. In other words, it canbe assumed that all shoes of a specific type, a specific manufacturershoe size and a specific manufacturer have an approximately identicalshoe inner length L.

FIG. 2A shows the distribution of the frequency H of the shoe innerlength L of the women's ankle boots for the three shoe sizes EU 37(curve S37), EU 38 (curve S38) and EU 39 (curve S39) for shoes ofdifferent manufacturers. The frequency distributions S37, S38, S39clearly overlap, the measured shoe inner length S is scattered overseveral neighboring shoe sizes. One respective binary membershipfunction can be determined from the one-dimensional frequencydistribution for each of the shoe sizes. This is shown in FIG. 2B. Z37refers here to the membership function for shoe size EU 37, Z38 to themembership function for shoe size EU 38, and Z39 to the membershipfunction for shoe size EU 39. The center of the membership functionsZ37, Z38, Z39 can be determined on the basis of the center of thecorresponding frequency distributions S37, S38 and S39, respectively,and can be centered on the maximum value of the respective frequencydistribution S37, S38, S39.

The width of the membership functions Z37, Z38, Z39 which may beidentical for all membership functions, may be chosen such that the shoeinner lengths L of the appropriate shoe size occurring most frequentlyare within the membership function Z37, Z38, Z39. The width of themembership function Z37, Z38, Z39 may for example be chosen such that atleast 50% or 90% of the shoes of the appropriate shoe size are withinthe respective membership function. The width of the membershipfunctions Z37, Z38, Z39 and the limit value can of course be fixedarbitrarily and on the basis of the respectively measured distributionof the frequency H. It is possible to determine such a membershipfunction for each manufacturer shoe size offered. The new shoe size 37now comprises for example all shoe inner lengths L of 23.7 cm (leftborder) up to the middle of the interval between the membership functionZ37 and Z38 of the new shoe size 38, 26.0 cm in the example. The newshoe size 38 includes shoe inner lengths L of 26.1 cm up to 26.8 cm, andthe new shoe size 39 includes shoe inner lengths L of 26.9 cm up to 30.7cm.

A new allocation of the shoe sizes is then carried out. On the basis ofthe measured shoe inner lengths L, outliers of the respectiveneighboring shoe size are assigned, the designation of the manufacturershoe sizes, i.e. EU 37, EU 38 etc. for example, being maintained ascategories of this new categorization. Due to this virtual re-labelingof the shoes which can for example be carried out using an appropriatedatabase, the shoe inner lengths L within the new shoe sizes arehomogenized, wherein the overlapping of the frequency distributions ofneighboring shoe sizes is reduced.

FIG. 3 shows a two-dimensional frequency distribution for twoanatomically relevant quantities, namely the shoe inner length L and theball circumference B. The frequency H is represented in a 2D-plot forshoe sizes EU 38 and EU 39. According to one example embodiment, amethod of categorizing the appropriate shoes using this two-dimensionalfrequency distribution is to be explained with reference to FIG. 4.

FIG. 4A shows the individual measurement results for the shoe innerlength L and the ball circumference B in a scatter diagram, i.e. theprojection of the 2D-histogram on a base area. Each point entrycorresponds to the inner dimension pair composed of the shoe innerlength L and the ball circumference B of an ankle boot of the shoe sizesconsidered and for one of the 51 manufacturers considered by way ofexample. The pairs of values for the manufacturer shoe size EU 38 areillustrated by open circles, those for the manufacturer shoe size EU 39by closed circles. The large scattering and overlapping of the frequencydistributions are clearly visible. For reasons of clarity, therepresentation is limited to two manufacturers and to shoe sizes EU 38and EU 39. In FIG. 4B, two-dimensional membership regions Z38 and Z39have been defined for each shoe size EU 38 and EU 39 on the basis of thepairs of values occurring most frequently of the shoe inner length L andthe ball circumference B. The membership regions Z38 and Z39 are chosenin the form of circles by way of example. Any further appropriate shapefor the membership regions Z38, Z39 is of course possible.

A categorization of the shoes may then be carried out. This is shown inFIG. 4C. The new shoe sizes can be assigned to the shoes using themembership regions such that the resulting frequency distribution inthese new shoe sizes shows a reduced intra-class variance and anincreased inter-class variance. In this context, the shoe size isconsidered as a class. This may be obtained in two agglomeration steps.The shoe size is maintained for all pairs of values within a membershipregion. The pairs of values outside the membership region are assignedto the next membership regions and, if necessary, are re-allocated. Allpairs of values designated by a not circled arrow are assigned to a newshoe size corresponding to the previous manufacturer shoe size. Thepairs of values designated by an encircled arrow are assigned to a newshoe size which differs from the original manufacturer shoe size. Theassignment of the new shoe size can for example be performed bycalculating a distance between the pair of values and a center ormaximum (cf. also FIG. 3) of the neighboring shoe sizes. Thecorresponding pair of values is now assigned to that shoe size fromwhich the distance is the smallest.

A skilled person in the field of statistics and in particular of clusteranalysis and classification knows to add further inner dimensionsanatomically relevant to the fit, such as the big toe angle, the heelheight, the height profile of the footbed etc. to the inner shapeparameters such as shoe inner length L and the ball circumference B, andto evaluate the described frequency functions in appropriately higherdimensional value spaces.

With a device for categorizing articles of clothing according to afurther example embodiment, the re-allocation of the shoe size asdescribed above may be carried out automatically, wherein themanufacturer shoe sizes of different manufacturers are “virtuallyre-labeled” using a database, for example. This is particularlyadvantageous for the online mail-order business, as explained by way ofexample below.

A female client orders a pair of women's ankle boot at the mail-orderbusiness. She knows her usual shoe size (for example EU 38) from formerorders or from her fitting footwear. The mail-order company offerswomen's ankle boots of different manufacturers. They may differ for thesame labeled shoe size in material, color, fashion accessories, priceetc. The client desires to order a fitting shoe according to shoe sizeEU 38 from this range of goods. The shoe sizes used by the manufacturersare very different due to the labeling characteristics of the respectivemanufacturers or of the last manufacturers thereof. Due to the alreadyperformed categorization, the mail-order company however knows that forthe different manufacturers the labeled manufacturer shoe size EU 38 maybe very different with regard to the actual shoe shape and the interiordimensions thereof. Therefore, many difficulties as to the fit must beexpected if the client orders a model merely in accordance with hersearch criterion “shoe size EU 38”.

According to an example embodiment, the mail-order company however hasgeometrically measured all women's ankle boots of its differentmanufacturers using a 3D-interior scanner and has determined on thisbasis a statistic (for all manufacturers) of the actually occurringinner shapes for each labeled manufacturer shoe size. The inner shape ofthe shoes is preferably described by the manufacturer using dimensionssuch as the shoe inner length L, the ball circumference B etc. Thesupplier thus has a frequency distribution comparable with that of FIG.1, 2A or 3.

According to the invention, these histograms of the shoe inner lengths Lare used as follows: The regions about the maxima are the shoe innerlengths L for a given shoe size (for all manufacturers) occurring mostfrequently. When selecting a shoe on the basis of the highly scatteringmanufacturer shoe size, the probability for the ordering client is thehighest to encounter a shoe inner length L in the region of thehistogram maximum. These regions of maximum frequency are thus definedas region of the shoe inner length L in which the standards shoe size ofthe client is most likely to match with the shoe size labeled by themanufacturer. Shoe inner lengths L outside these regions of maximumfrequency are virtually re-labeled in neighboring shoe sizes by themail-order company, and these re-labeled sizes are used for theselection of the best fitting shoe.

A particular advantage of the method consists in that the expenditure onthe part of the ordering client is not increased despite the improvementof the obtainable fit rate. The client does not require any additionalanatomical features of his/her foot beyond the classical shoe size. Theefforts to be made remain to the mail-order company, which can integratethe method according to the invention in its electronic orderingprocedure.

It is left to the mail-order company whether it communicates theperformed categorization to the client, for example by specificationssuch as: “We recommend you for your shoe size “38” and this manufacturer“X” to order a shoe size “39””, or if the selection of the fitting shoewith the re-labeled shoe sizes remains invisible for the buyer.

The method according to aspects of the invention is not limited to themail-order business of shoes. It may also be advantageously applied tothe conventional shoe selling, i.e. in the shoe shop to reduce thenumber of potentially fitting shoes prior to the actual trying on andthus to accelerate the selling process. The allocation of the shoe sizescan be carried out by means of a database on site or by means of anoutsourced database, an assignment table e.g., and positively limit thechoice of possibly fitting shoes.

The method according to aspects of the invention is not limited to theselection of footwear, but may also be applied advantageously in asimilar manner to the clothing commerce. Also here, the problem is knownthat manufacturer clothing sizes are assigned in an unsystematic manner,vary and are little consistent with standard sizes. Instead of a shoeinterior scanner, a body scanner may be used to determine the frequencydistributions of the different body dimensions such as waistcircumference, length of leg, chest measurement etc. Using the methodaccording to the invention, a considerably smaller dispersion within thenewly allocated clothing size and a considerably reduced overlappingbetween the different clothing sizes may be obtained.

1: A method of categorizing articles of clothing with regard to theirclothing size describing a fit and/or a size of the article of clothing,each article of clothing being provided with a manufacturer clothingsize determined on the part of the manufacturer, a basic populationbeing considered which comprises articles of clothing having differentmanufacturer clothing sizes, and articles of clothing of differentmanufacturers being included in each manufacturer clothing size, themethod comprising the following steps: a) acquiring at least oneparameter describing the fit and/or the size of an article of clothingon the basis of a measurement carried out on the article of clothingconcerned, b) assigning the acquired parameter to the manufacturerclothing size of the measured article of clothing, c) performing thesteps a) and b) for a plurality of articles of clothing of differentmanufacturers having an identical manufacturer clothing size, d)performing the steps a) to c) for a plurality of different manufacturerclothing sizes, e) performing a frequency analysis for the occurrence ofspecific values of the at least one parameter for articles of clothingof different manufacturers having an identical manufacturer clothingsize, the frequency analysis being performed for a plurality ofmanufacturer clothing sizes, f) categorizing the articles of clothing bya new allocation of the clothing size, the new clothing size beingallocated to the articles of clothing in such a manner that the at leastone parameter of articles of clothing provided with the new clothingsize within this new clothing size has a smaller dispersion than the atleast one parameter acquired as to the manufacturer clothing size. 2:The method of categorizing articles of clothing according to claim 1,wherein a statistical key figure characterizing the frequencydistribution for the at least one parameter from the respectivefrequency distribution is determined for each of the manufacturerclothing sizes considered and is allocated thereto, and wherein in stepf), a deviation of the at least one parameter of an article of clothingto be categorized from the corresponding statistical key figure of thisparameter for articles of clothing of different manufacturers and havingdifferent manufacturer clothing sizes is determined, and wherein thatnew clothing size is allocated to the article of clothing, for which thedeviation from the statistical key figure is minimal. 3: The method ofcategorizing articles of clothing according to claim 2, wherein thestatistical key figure characterizing the frequency distribution is apercentile value of the frequency distribution and/or a mean value ofthe frequency distribution. 4: The method of categorizing articles ofclothing according to claim 1, wherein step a) is performed on identicalor similar articles of clothing of different manufacturers, at least onearticle of clothing being respectively measured representatively for amanufacturer clothing size of a manufacturer considered, and wherein instep f), a categorization is carried out for all articles of clothing ofthe considered manufacturer clothing size of the correspondingmanufacturer. 5: The method of categorizing articles of clothingaccording to claim 1, wherein the articles of clothing are shoes and themanufacturer clothing size is a manufacturer shoe size assigned on thepart of the manufacturer, wherein, to reduce a negative influence on thefit as a result of inner shape deviations despite an identicalmanufacturer shoe size, in step a), an inner shape of a shoe is acquiredand at least one parameter describing the dimension of the shoe interioris determined, in step b), the at least one parameter of themanufacturer shoe size is assigned, steps a) and b) are performed foridentical or similar shoe models from the production of differentmanufacturers and for different manufacturer shoe sizes, in step e), afrequency analysis for the occurrence of specific values of the at leastone parameter is performed for shoes of different manufacturers buthaving an identical manufacturer shoe size, and in step f), acategorization of the shoes is performed by a new assignment of the shoesize, the new shoe size being allocated to the shoes such that the atleast one parameter of the shoes provided with the new shoe size withinthe new shoe size has a smaller dispersion than in the originalmanufacturer shoe size. 6: The method of categorizing articles ofclothing according to claim 5, wherein in step a), at least one shoe pershoe model and per manufacturer shoe size is measured in arepresentative manner for the shoe model and the manufacturer shoe sizeusing a shoe interior scanner, and at least one anatomically relevantquantity is acquired as parameter describing the dimension of the shoeinterior, in step e), a one-dimensional frequency function is formed forthe chosen anatomically relevant quantity, a membership function isfixed, which defines a range of values of the anatomically relevantquantity in question, and this membership function is allocated to a newshoe size, and in step f), a categorization of the shoes is performed bya new allocation of the shoe size, such that the one-dimensionalfrequency function of the parameter describing the anatomically relevantquantity within the new shoe size has a smaller dispersion than in theoriginal manufacturer shoe size. 7: The method of categorizing articlesof clothing according to claim 5, wherein in step a), at least one shoeper shoe model and per manufacturer shoe size is measured using a shoeinterior scanner, and n>=2 interior dimensions are extracted from thesemeasurements, in step d), an n-dimensional frequency function per shoesize and per manufacturer is established for the n chosen anatomicalquantities, an n-dimensional membership function is fixed which definesa range of values of the n anatomical quantities, and in step f), theshoe sizes for all manufacturers considered are reallocated such thatthe n interior dimensions within the new shoe sizes have a smallerdispersion than in the original manufacturer shoe sizes. 8: The methodof categorizing articles of clothing according to claim 1, wherein thearticles of clothing are protective clothing or medical parts adapted tothe body, such as supports, splints or protectors. 9: A method ofselecting footwear having an improved fit, wherein shoe sizes arereassigned in accordance with a categorizing method according to claim5, and wherein shoes the new shoe size of which corresponds to therequest of the user are offered to a user on request for a specific shoesize. 10: A device for categorizing articles of clothing with regard totheir clothing size which describes a fit and/or a size of the articleof clothing, each article of clothing being provided with a manufacturerclothing size determined on the part of the manufacturer, and wherein abasic population is considered which comprises articles of clothinghaving different manufacturer clothing sizes and articles of clothing ofdifferent manufacturers are included in each manufacturer clothing size,and wherein the device comprises a scanner for acquiring at least oneparameter describing the fit and/or the size of an article of clothing,and a processing unit, the processing unit being adapted a) to assignthe at least one acquired parameter to the manufacturer clothing size,b) to perform a frequency analysis for the occurrence of specific valuesof the at least one parameter for articles of clothing of differentmanufacturers having an identical manufacturer clothing size, and toperform the frequency analysis for a plurality of articles of clothingof different manufacturers but having an identical manufacturer clothingsize, and for different manufacturer clothing sizes, and c) tocategorize the articles of clothing by a new allocation of the clothingsize and to allocate the new clothing size to the articles of clothingsuch that the at least one parameter of the articles of clothingprovided with the new clothing size within the new clothing size has asmaller dispersion than in the original manufacturer clothing size. 11:The device for categorizing articles of clothing according to claim 10,wherein the articles of clothing are shoes and the manufacturer clothingsize is a manufacturer shoe size assigned on the part of themanufacturer, and wherein the scanner is a scanner for detecting aninner shape of shoes and is further adapted to determine at least oneparameter describing the dimension of the shoe interior, and theprocessing unit being further adapted: in feature a), to assign the atleast one parameter to the manufacturer shoe size, in feature b), toperform a frequency analysis for the occurrence of specific values ofthe at least one parameter for shoes of different manufacturers havingan identical manufacturer shoe size, and in feature c), to carry out acategorization of the shoes by a new allocation of the shoe size,wherein a new shoe size is allocated to the shoes in such a manner thatthe at least one parameter of the shoes provided with the new shoe sizewithin the new shoe size has a smaller dispersion than in the originalmanufacturer shoe size. 12: A device for selecting footwear having animproved fit, comprising a device for categorizing articles of clothingaccording to claim 11 and an input and output unit, the input unit beingadapted to receive information about a shoe size requested by a user,and the processing unit being adapted to offer the user informationabout footwear the new shoe size of which corresponds to the shoe sizerequested by the user via the output unit. 13: A method of selectingfootwear having an improved fit, wherein shoe sizes are reassigned inaccordance with a categorizing method according to claim 6, and whereinshoes the new shoe size of which corresponds to the request of the userare offered to a user on request for a specific shoe size. 14: A methodof selecting footwear having an improved fit, wherein shoe sizes arereassigned in accordance with a categorizing method according to claim7, and wherein shoes the new shoe size of which corresponds to therequest of the user are offered to a user on request for a specific shoesize.